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Single-cell spatial proteomics. | LitMetric

Single-cell spatial proteomics.

Histol Histopathol

Biodesign Institute and School of Molecular Sciences, Arizona State University, Tempe, Arizona, USA.

Published: December 2024

AI Article Synopsis

  • Recent advancements in single-cell spatial proteomics are changing how we understand cellular signaling in health and disease, with a focus on mass spectrometry (MS) imaging and multiplexed immunofluorescence (mIF).
  • These technologies allow for detailed protein profiling at the single-cell level, revealing cellular diversity, organization, and functions in their natural environments.
  • The review notes current challenges and potential solutions with these methods and suggests that combining spatial proteomics with other biological approaches could improve our understanding of complex systems and lead to better diagnostics and personalized treatments.

Article Abstract

Recent advancements in single-cell spatial proteomics have revolutionized our ability to elucidate cellular signaling networks and their implications in health and disease. This review examines these cutting-edge technologies, focusing on mass spectrometry (MS) imaging and multiplexed immunofluorescence (mIF). Such approaches allow high-resolution protein profiling at the single-cell level, revealing intricate cellular heterogeneity, spatial organization, and protein functions within their native cellular contexts. MS imaging techniques offer unprecedented high-dimensional resolution and provide detailed insights into their subcellular protein localization and abundance. mIF enables rapid and high-throughput protein profiling, enhancing its accessibility for diverse research and clinical applications. This review assesses the current challenges associated with these methodologies and also discusses the potential solutions to overcome these obstacles. The integration of spatial proteomics with other systems biology approaches holds great promise for enhancing our understanding of complex biological systems. It could also lead to significant advancements in molecular diagnostics and personalized treatment strategies.

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Source
http://dx.doi.org/10.14670/HH-18-861DOI Listing

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